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      Alteration of Gut Microbial Metabolites in the Systemic Circulation of Patients with Parkinson’s Disease

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          Abstract

          Background: Emerging evidence suggests that gut dysbiosis contributes to Parkinson’s disease (PD) by signaling through microbial metabolites. Hippuric acid (HA), indole derivatives, and secondary bile acids are among the most common gut metabolites. Objective: To examine the relationship of systemic concentrations of these microbial metabolites associated with changes of gut microbiota, PD status, and severity of PD. Methods: We enrolled 56 patients with PD and 43 age- and sex-matched healthy participants. Motor and cognitive severity were assessed with Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) part III motor score and the Mini-Mental State Examination (MMSE), respectively. Plasma concentrations of targeted gut metabolites were measured with liquid chromatography-tandem mass spectrometry. Gut microbiota was analyzed with shotgun metagenomic sequencing. Results: Compared with controls, PD patients had significantly higher plasma levels of HA, indole-3-propionic acid (IPA), deoxycholic acid (DCA), and glycodeoxycholic acid (GDCA). After adjustment for age and sex in a multivariate logistic regression analysis, plasma levels of HA (odds ratio [OR] 3.21, p < 0.001), IPA (OR 2.59, p = 0.031), and GDCA (OR 2.82, p = 0.036) were associated with positive PD status. Concentrations of these gut metabolites did not correlate with MDS-UPDRS part III score or MMSE after adjustment for confounders. Microbial metabolite levels were associated with the relative abundance of pro-inflammatory gut bacteria. Conclusion: Aberrant gut microbial metabolites of HA, indole derivatives and secondary bile acids associated with specific gut microbiota changes were observed in patients with PD.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Improved metagenomic analysis with Kraken 2

            Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.
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              Staging of brain pathology related to sporadic Parkinson’s disease

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                Author and article information

                Journal
                Journal of Parkinson's Disease
                JPD
                IOS Press
                18777171
                1877718X
                May 24 2022
                May 24 2022
                : 12
                : 4
                : 1219-1230
                Affiliations
                [1 ]Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
                [2 ]Department of Neurology, National Taiwan University Hospital Bei-Hu Branch, Taipei, Taiwan
                [3 ]Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
                [4 ]Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
                [5 ]School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan.
                [6 ]Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
                [7 ]The Metabolomics Core Laboratory, NTU Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan
                [8 ]Department of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan
                Article
                10.3233/JPD-223179
                35342048
                58119304-ada4-4d74-b400-1d0b01cfa454
                © 2022
                History

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